MOSFET建模的SPICE优化人工智能技术

2009 Innovative Technologies in Intelligent Systems and Industrial Applications Pub Date : 2009-07-25 DOI:10.1109/CITISIA.2009.5224238

J. E. Suseno, M. Riyadi, N. Alias, Y. W. Heong, R. Ismail

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引用次数: 1

摘要

本文提出了利用人工神经网络优化和验证MOSFET电特性图的新方法。利用神经网络(ONN)进行优化，比较TCAD仿真和TSPICE建模之间的电流-电压(I-V)特征图，作为期望数据控制BSIM的模型参数。本文采用的神经网络方法是动态前馈神经网络。经过神经网络训练，得到的最佳结果是36-30-10-5的神经网络结构，在epoch为5时的均方误差(MSE)为1e-28。

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Artificial intelligence techniques for SPICE optimization of MOSFET modeling

This paper proposes new method for optimize and verified electric characterization graph of MOSFET by using artificial neural network. Optimization using Neural Network (ONN) will compare current-voltage (I–V) Characteristic graph between the TCAD simulation and TSPICE modeling as desire data control a model parameter of BSIM. In this paper, the neural network method is dynamic feedforward Neural Network. After NN training, the best result is at Neural Network architecture of 36-30-10-5 with Mean Squared Error (MSE) of 1e-28 at epoch of 5.

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来源期刊

2009 Innovative Technologies in Intelligent Systems and Industrial Applications

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